The use of a pulse of light to measure distance is well known. As is commonly used in devices such as a police speed detector, the basic concept is that of pulsing a laser emitter, which causes a burst of light to be emitted, usually focused through a lens or lens assembly. Then, the time it takes for that pulse of light to return to a detector mounted near the emitter is measured, and a distance can then be derived from that measurement with high accuracy.
When multiple pulses are emitted in rapid succession, and the direction of those emissions is somehow sequentially varied, each distance measurement can be considered a pixel, and a collection of pixels emitted and captured in rapid succession (called a “point cloud”) can be rendered as an image or analyzed for other reasons such as detecting obstacles. Viewers that render these point clouds (today typically PC based) can manipulate the view to give the appearance of a 3-D image. While the data that comes back is lacking color or other characteristics, different schemes can be used to depict the distance measurements that allow the rendering device to show the 3-D image as if it were captured by a live action camera.
There exist a number of commercial products that can capture distance points in rapid succession and render a 2-D (i.e. single plane) point cloud. These instruments are often used in surveying, mapping, autonomous navigation, industrial applications, and for other purposes. Most of these devices rely on the use of a single laser emitter/detector combination combined with some type of moving mirror to effect scanning across at least one plane, as shown in FIG. 1.
Such devices are often used in industrial applications, as shown in FIG. 2. Note the scan lines emitting from the unit—the spinning mirror allows the single laser emitter/detector assembly to be aimed along this plane via the use of the rotating mirror.
Often, these mirrors are rotated at very fast speeds—in the thousands of RPMs. As stated above, this design inherently renders only a 2-D point cloud. However, a 3-D point cloud is often required. The other dimension is provided for in a number of ways. Most often, the entire instrument is actuated up and down and/or back and forth, often on a gimbal—a process know within the art as winking or nodding the sensor. Thus, a single beam lidar unit can be employed to capture an entire 3-D array of distance points, albeit one point at a time. An example of this approach is shown in FIG. 3. FIG. 3 shows a 2-D scanner employing a single laser emitter/detector pair and a rotating mirror mounted on a gimbal that “nods” the unit up and down, and rotates it back and forth in order to increase field of view.
In yet other single laser emitter/detector pair mirror-based prior art devices there exists a prism that “divides” the laser pulse into multiple “layers,” with each layer having a slightly different vertical angle. This simulates the nodding effect described above but with no need for actuation of the sensor itself.
In all the above examples, the main premise is a single laser emitter/detector combination, where the light path is somehow altered to achieve a broader field of view than a single sensor can achieve. The device is inherently limited to the number of pixels it can generate due to the limitation of how many pulses per second are possible from a single laser. Any alteration of the laser's path, whether it is by mirror, prism, or actuation of the device, causes the point cloud to be less dense, but cover a broader area. The goal for sensors of this nature is to maximize the number of pixels to provide a point cloud that covers a broad field of view yet is as dense as possible.
It is of course possible to add additional lasers and detectors to a rotating mirror unit. While this can easily be done, the resultant performance does not necessarily scale with the number of lasers used. When multiple laser emitter/detector combinations are employed for a spinning mirror scanner, or when the single laser is divided via the use of a prism, the image also rotates. Therefore, while the beams will fan out vertically in one direction, they will twist so as to align horizontally in the 90-degree rotational direction. While this arrangement can be used for forward-looking-only units, it is less than desirable if a sideways view is also desirable, as is often the case for many applications.
There also exist “flash lidar” units. These operate by simultaneously illuminating a large area, and capturing the resultant pixel-distance information on a specialized 2-D focal plane array (FPA). Such sensors are complicated and difficult to manufacture, and as a result not widely deployed commercially. However, it is expected that they will someday replace the mechanically scanned sensors, as they are solid state, and require no moving parts. FIG. 4 shows the framework for the detector array of a flash lidar unit.
It is always desirable to collect more points faster. Until flash lidar technology is perfected, there will always be a compromise of sensors that alter the path of the emitter/detector beam in order to achieve a broader field of view.
As noted above, 3-D point cloud systems exist in several configurations, the needs for autonomous vehicle navigation place unrealistic demands on current systems. For example, there are numerous systems that take excellent pictures, but take several minutes to collect a single image. Such systems are unsuitable for highway use. There are also flash systems that have excellent update rate but lack field of view lack and good distance performance. There are single beam systems that can provide useful information but do not work well with objects that are too small and fall outside the unit's field of view. In reality, it is necessary to see everywhere around the vehicle, almost a full 360 degrees, in order to safely navigate today's highways. In addition, it is necessary to have a minimum of delay between the actions happening in the real world and the imaging/reaction to it. Generally, it is accepted that human response time is in the several tenths of a second. Therefore, it is realistic to provide the navigation computer with a complete fresh update approximately ten times a second. Of course, faster is better, but it may also be possible to navigate successfully with an update rate of 5 times a second. The vertical field of view needs to extend above the horizon, in case the car enters a dip in the road, and should extend down as close as possible to see the ground in front of the vehicle. Of course, it is not possible to see directly in front of the vehicle, since the hood or other parts of the car obstruct the view.
While the preferred embodiment uses 64 discrete vertical beams to capture the point cloud data, as few as 16 beams or fewer could be employed, with largely the same result. In addition, it is preferable to disperse the beams such that there is coverage that is more detailed directly horizontally in front of the vehicle, such concentration being useful for highway driving at speed.